Synthesis in Estuarine and Coastal Ecological Research: What Is It,Why Is It Important,and How Do We Teach It?

During the last two decades, there has been growing interest in the integration of existing ideas and data to produce new synthetic models and hypotheses leading to discovery and advancement in estuarine and coastal science. This essay offers an integrated definition of what is meant by synthesis research and discusses its importance for exploiting the rapid expansion of information availability and for addressing increasingly complex environmental problems. Approaches and methods that have been used in published synthetic coastal research are explored and a list of essential steps is developed to provide a foundation for conducting synthetic research. Five categories of methods used widely in coastal synthesis studies are identified: (1) comparative cross-system analysis, (2) analysis of time series data, (3) balance of cross-boundary fluxes, (4) system-specific simulation modeling, and (5) general systems simulation modeling. In addition, diverse examples are used to illustrate how these methods have been applied in previous studies. We discuss the urgent need for developing curricula for classroom and experiential teaching of synthesis in coastal science to undergraduate and graduate students, and we consider the societal importance of synthetic research to support coastal resource management and policy development. Finally, we briefly discuss the crucial challenges for future growth and development of synthetic approaches to estuarine and coastal research.     

Hydraulic tomography analysis of municipal-well operation data with geology-based groundwater models

The sustainable management of groundwater resources is essential to municipalities worldwide due to increasing water demand. Planning for the optimized use of groundwater resources requires reliable estimation of hydraulic parameters such as hydraulic conductivity (K) and specific storage (S_s). However, estimation of hydraulic parameters can be difficult with dedicated pumping tests while municipal wells are in operation. In this study, the K and S_s of a highly heterogeneous, multi-aquifer/aquitard system are estimated through the inverse modeling of water-level data from observation wells collected during municipal well operations. In particular, four different geological models are calibrated by coupling HydroGeoSphere (HGS) with the parameter estimation code PEST. The joint analysis of water-level records resulting from fluctuating pumping and injection operations amounts to a hydraulic tomography (HT) analysis. The four geological models are well calibrated and yield reliable estimates that are consistent with previously studies. Overall, this research reveals that: (1) the HT analysis of municipal well records is feasible and yields reliable K and S_s estimates for individual geological units where drawdown records are available; (2) these estimates are obtained at the scale of intended use, unlike small-scale estimates typically obtained through other characterization methods; (3) the HT analysis can be conducted using existing data, which leads to substantial cost savings; and (4) data collected during municipal well operations can be used in the development of new groundwater models or in the calibration of existing groundwater models, thus they are valuable and should be archived.

     

Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study

A critical prerequisite of risk prevention measures for natural hazards is from the results of forensic disaster investigations (FDIs). The current studies of the FDIs are limited by data issues including data availability and data reliability. The applications of crowdsourcing method in natural disasters indicate the potential to provide data support for the FDIs. However, there is very limited existing research on the use of crowdsourcing data for the FDIs. Following the requirements published by the Integrated Research on Disaster Risk program for FDIs, this paper establishes the process map for conducting the FDIs by scenario analysis approach with the crowdsourcing and crowdsensor data. Hurricane Harvey is used as the case study to implement the process map. The results show that the use of crowdsourcing data for the FDIs is feasible. Though this paper takes practical measures for improving the reliability of crowdsourcing data (i.e., little data size) in the case study, future research can focus on the development of advanced algorithm for the crowdsourcing data quality validation.     

Spatial Modeling Techniques for Characterizing Geomaterials:Deterministic vs.Stochastic Modeling for Single-Variable and Multivariate Analyses

Sample data in the Earth and environmental sciences are limited in quantity and sampling location and therefore, sophisticated spatial modeling techniques are indispensable for accurate imaging of complicated structures and properties of geomaterials. This paper presents several effective methods that are grouped into two categories depending on the nature of regionalized data used. Type I data originate from plural populations and type II data satisfy the prerequisite of stationarity and have distinct spatial correlations. For the type I data, three methods are shown to be effective and demonstrated to produce plausible results: (1) a spline-based method, (2) a combination of a spline-based method with a stochastic simulation, and (3) a neural network method. Geostatistics proves to be a powerful tool for type II data. Three new approaches of geostatistics are presented with case studies: an application to directional data such as fracture, multi-scale modeling that incorporates a scaling law, and space-time joint analysis for multivariate data. Methods for improving the contribution of such spatial modeling to Earth and environmental sciences are also discussed and future important problems to be solved are summarized.      

Long-term biological data sets: Their role in research,monitoring, and management of estuarine and coastal marine systems

Long-term records of biological data are extremely valuable for documenting ecosystem changes, for differentiating natural changes from those caused by humans, and for generating and analyzing testable hypotheses. Long-term sampling, however, is generally discouraged by a variety of institutional disincentives, so that today such records are uncommon. We discuss approaches for overcoming these disincentives through improved research planning and design, including clearera priori definition of management and regulatory actions and information needs, more rigorous adherence to hypothesis formulation and testing, and proper spatial and temporal scaling in sampling. We distinguish between prospective study design, in which the foregoing elements are essential for coast-effectiveness, and retrospective analysis, which relies on reconstruction of long-term records from existing data sets. We demonstrate the great value of retrospective analysis of encountered data, and argue for renewed attention to archival of data sets with documented data quality, interacalibration and documentation of methodologies, and long-term storage of samples for future analysis. Such practices are essential to ensure the quality of long-term records that are reconstructed for retrospective examination of new hypotheses in the future.     

Improvements in storm surge surrogate modeling for synthetic storm parameterization,node condition classification and implementation to small size databases

Surrogate models are becoming increasingly popular for storm surge predictions. Using existing databases of storm simulations, developed typically during regional flood studies, these models provide fast-to-compute, data-driven approximations quantifying the expected storm surge for any new storm (not included in the training database). This paper considers the development of such a surrogate model for Delaware Bay, using a database of 156 simulations driven by synthetic tropical cyclones and offering predictions for a grid that includes close to 300,000 computational nodes within the geographical domain of interest. Kriging (Gaussian Process regression) is adopted as the surrogate modeling technique, and various relevant advancements are established. The appropriate parameterization of the synthetic storm database is examined. For this, instead of the storm features at landfall, the features when the storm is at closest distance to some representative point of the domain of interest are investigated as an alternative parametrization, and are found to produce a better surrogate. For nodes that remained dry for some of the database storms, imputation of the surge using a weighted k nearest neighbor (kNN) interpolation is considered to fill in the missing data. The use of a secondary, classification surrogate model, combining logistic principal component analysis and Kriging, is examined to address instances for which the imputed surge leads to misclassification of the node condition. Finally, concerns related to overfitting for the surrogate model are discussed, stemming from the small size of the available database. These concerns extend to both the calibration of the surrogate model hyper-parameters, as well as to the validation approaches adopted. During this process, the benefits from the use of principal component analysis as a dimensionality reduction technique, and the appropriate transformation and scaling of the surge output are examined in detail.

     

贺兰拗拉谷北段奥陶系等深流沉积

采用野外观察描述和室内分析相结合的方法,以桌子山剖面奥陶系沉积相研究为基础,识别出了典型的碳酸盐等深流沉积。首次采用Fischer图解法,求取了碳酸盐等深流沉积其可容空间变化曲线。参照野外的样品化学分析数据,得出深水等深岩的生烃能力较好,故对等深岩的研究具有潜在的矿产意义。在未来研究上,应运用地震波识别、遥感等现代科技调查手段,进行多学科综合研究,尽快建立一套完善的识别标志,以促使其逐渐成为沉积学中一个更为完善的研究领域。     

Research Progress of Modification of Reservoirs by Dissolution in Sedimentary Rock

With the deepening of exploration degree, the progress of exploration technology and the increasing demands for oil and gas resources, some deep buried reservoirs with relatively poor physical properties have attracted more and more attention of geologists. After decades of exploration, many high-quality reservoirs with shallow burial and well-preserved primary pores have been widely discovered and put into production. However, deep buried tight reservoirs with secondary dissolved pores as the main reservoir space are increasingly becoming the focus of exploration in mature exploration areas. Therefore, searching for secondary pore development zones and dissolved "sweet" reservoirs will become an important new field for fine exploration in the future. Based on some typical case studies and a large number of research results, this paper systematically expounded the modification of reservoirs by dissolution from the following four aspects:①Diagenetic stage of dissolution; ②Types of dissolution fluids;③Main controlling factors of dissolution; ④Effect of dissolution on reservoir modification. In recent years, more and more research achievements have made important progress in dissolution mechanism and reservoir modification effect. The systematic analysis of these mainstream views has some reference value for similar geological conditions in the future.     

Land use change modelling: current practice and research priorities

Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews current models to identify priority issues for future land use change modelling research. This discussion is based on six concepts important to land use modelling: (1) Level of analysis; (2) Cross-scale dynamics; (3) Driving forces; (4) Spatial interaction and neighbourhood effects; (5) Temporal dynamics; and (6) Level of integration. For each of these concepts an overview is given of the variety of methods used to implement these concepts in operational models. It is concluded that a lot of progress has been made in building land use change models. However, in order to incorporate more aspects important to land use modelling it is needed to develop a new generation of land use models that better address the multi-scale characteristics of the land use system, implement new techniques to quantify neighbourhood effects, explicitly deal with temporal dynamics and achieve a higher level of integration between disciplinary approaches and between models studying urban and rural land use changes. If these requirements are fulfilled models will better support the analysis of land use dynamics and land use policy formulation.     

冰川运动速度研究： 方法、 变化、 问题与展望

冰川运动将积累区获得的物质输送到消融区, 维持着冰川的动态平衡。近年来, 随着气候变化, 全球大部分冰川面临着剧烈的退缩, 而冰川运动变化则较为复杂, 引起了学者们的广泛关注。文章系统总结了近年来冰川运动速度的提取方法、 冰川运动速度时空分布与变化及其影响因素的相关研究进展。另外, 还探讨了目前冰川运动速度研究中存在的问题和未来的发展趋势。结果表明： 基于测杆的方法能够获得精度较高的测量数据, 但存在时间和空间上的局限性; 基于遥感数据自动化提取的方法应用广泛, 但影像之间的配准以及海量数据的计算是当前阶段制约冰川运动速度研究的主要问题; 近年来, 无人机和地基合成孔径雷达的应用为冰川运动速度研究提供了高精度的数据支撑, 但二者在冰川运动研究中的应用还不够广泛。冰川运动速度的分布及其变化在空间上存在明显差异, 冰川厚度的变化可能是全球大部分冰川运动速度变化的主要原因, 但在单个冰川系统上, 冰川运动速度变化较为复杂, 其原因还需要进一步探讨。遥感数据的不断丰富, 云计算平台的使用, 物联网、 无人机和地基合成孔径雷达等技术的不断普及, 以及星、 空、 地协同观测的出现将会极大促进未来冰川运动速度研究的发展。此外, 冰川动力学过程也将备受关注, 成为未来冰川运动研究的热点问题。     

古风暴学研究进展

古风暴学是始于20世纪90年代的一门新兴学科，通过研究风暴活动的地质记录和历史文献资料，恢复器测之前几百年至数千年前的热带气旋活动规律。经过十几年的发展，逐渐形成一套包括研究领域、方法、技术与手段等比较完整的理论体系，成为第四纪古气候研究和过去全球变化的重要组成部分。古风暴学研究的替代指标包括：文字记载、特征的风暴事件沉积、海相化石组合、同位素地球化学组成等。这些指标单独使用时都有一定局限性。寻找新的替代指标，并运用多种指标综合分析方法提高古风暴事件的分辨率和可信度，是今后该学科发展的重要方向。已有的研究多侧重于古风暴频数的研究，今后应充分利用现代风暴潮理论的新进展，通过数值模拟与替代指标研究相结合，更准确地恢复古风暴强度。同时，应加强古风暴活动的全球对比研究，以揭示风暴活动与全球气候变化的关系，为在全球不断变暖背景下台风活动的情景预测提供依据。     

A review of geoanalytical databases

Geoanalytical data provide fundamental information according to which the Earth’s resources can be known and exploited to support human life and development. Large amounts of manpower and material and financial resources have been invested to acquire a wealth of geoanalytical data over the past 40 years. However, these data are usually managed by individual researchers and are preserved in an ad hoc manner without metadata that provide the necessary context for interpretation and data integration requirements. In this scenario, fewer data, except for published data, can be reutilized by geological researchers. Many geoanalytical databases have been constructed to collect existing data and to facilitate their use. These databases are useful tools for preserving, managing, and sharing data for geological research, and provide various data repositories to support geological studies. Since these databases are dispersed and diverse, it is difficult for researchers to make full use of them. This contribution provides an introduction on available geoanalytical databases. The database content can be made accessible to researchers, the ways in which this can be done, and the functionalities that can be used are illustrated in detail. Moreover, constraints that have limited the reutilization of geoanalytical data and creation of more advanced geoanalytical databases are discussed.

     

Geospatial analyses of alcohol and drug problems: empirical needs and theoretical foundations

Over the past four decades geospatial analyses of alcohol and drug problems have moved to the forefront of ecological studies of the correlates and determinants of drug addictions in community health. These advances have been predicated upon the expanding computational capabilities of geographic information systems, advancement of statistical tools for the analysis of spatial data, and the formulation of suitable social ecological theory. This paper provides an introduction to the study of drug markets in the US as a model social problem for geospatial research and analysis. Market and epidemic models of the growth of the methamphetamine abuse and dependence in California are used as examples of two fruitful approaches to understanding the social processes that underlie use of this dangerous substance. Data on the growth of the epidemic are described and used to motivate theoretical and empirical concerns regarding further analyses of the development of drug markets over space and time. These concerns, in turn, begin to be addressed by the remaining four papers in this series, each providing some examples and insights into avenues of geospatial research which can be profitably explored in the future.     

Is VGI participation? From vernal pools to video games

This paper examines the relationship between public participatory GIS (PPGIS) and volunteered geographic information (VGI). A brief review of the history of PPGIS reveals similarities between the two but also provides examples of how these two areas have developed in ways that cause the boundaries between them to be unclear at times. As evidence for advancing this conversation, 2 case studies are presented: volunteers mapping vernal pools and park design in Second Life. These case studies demonstrate both the intertwined nature of some aspects of VGI and PPGIS, while also showing some aspects of divergence.     

Urban form study: the sprawling city—review of methods of studying urban sprawl

There is a large body of research on urban forms. This review paper focuses on the urban sprawl using new and old approaches and new techniques from the subfield of urban Geography. There has been a debate among researchers about the definition of the sprawl, which makes it difficult to suggest a reliable model of the urban sprawl. This review is extremely selective. Numerous papers have focused on measuring the in terms of its physical cost or the environmental and transportation measures linked to this phenomenon. Several attempts have been made to improve the measurement of the sprawl using new approaches. Furthermore, this paper show that certain researchers did not attempt to explore new methods to investigate the urban sprawl in the past and present overlay layers for many years, researchers may use cartography techniques, for example, thereby collecting 20 years of data to match layers and show the differences in any metropolitan area. Several problems remain like differences in the understanding of the sprawl among planners and between other researchers interested in this issue. Also, it is problematic to find one measure, such as mixing different measures together to distinguish between car density and resident density. This study evaluated and reviewed old and recent studies to show that the most important issue in the urban sprawl relates to measurements. Incorporates inform and which measure is best. This article argues that urban spatial expansion reviews some of articles written on urban sprawl and showing the different approaches to studying.

     

LandScan USA: a high-resolution geospatial and temporal modeling approach for population distribution and dynamics

High-resolution population distribution data are critical for successfully addressing important issues ranging from socio-environmental research to public health to homeland security, since scientific analyses, operational activities, and policy decisions are significantly influenced by the number of impacted people. Dasymetric modeling has been a well-recognized approach for spatial decomposition of census data to increase the spatial resolution of population distribution. However, enhancing the temporal resolution of population distribution poses a greater challenge. In this paper, we discuss the development of LandScan USA, a multi-dimensional dasymetric modeling approach, which has allowed the creation of a very high-resolution population distribution data both over space and time. At a spatial resolution of 3 arc seconds (～90 m), the initial LandScan USA database contains both a nighttime residential as well as a baseline daytime population distribution that incorporates movement of workers and students. Challenging research issues of disparate and misaligned spatial data and modeling to develop a database at a national scale, as well as model verification and validation approaches are illustrated and discussed. Initial analyses indicate a high degree of locational accuracy for LandScan USA distribution model and data. High-resolution population data such as LandScan USA, which describes both distribution and dynamics of human population, clearly has the potential to profoundly impact multiple domain applications of national and global priority.     

多点地质统计学建模研究进展

从精细油藏描述中地质建模的意义和现状入手,介绍了多点地质统计学建模研究现状及其与传统地质建模方法的差 异。以辽河盆地西部凹陷某蒸汽驱试验区为例,分析了多点地质统计学建模中建模的基础、训练图像的建立、多点地质统计学 建模与传统地质建模相比所具有的优势等内容。指出多点地质统计学在井间预测方面具有明显优于其他传统建模方法的特 点。在文献调研基础上,结合自身工作实践,探讨了多点地质统计学建模目前存在的问题和未来的发展方向。指出未来多点 地质统计学建模的发展方向主要包括多信息综合地质成因分析基础上的训练图像获取、多点地质统计学算法进行改进和完善 和多点地质统计学建模方法应用领域的扩大等。     

结构方程模型在地球化学数据分析中的应用

为了实现通过确定地球化学组合元素来反映成矿异常, 本文在主成分分析模型的基础上, 引入了新的结构方程模型(SEM).与主成分所不同的是, 结构模型综合了经典统计方法中的因子分析和路径分析方法, 以与研究对象具有较好的拟合度为标准来确定最优解, 并通过模型最优解来确定新的成分组合, 因此结构模型所确定的成分变量不一定是具有最大变化性, 而是与研究对象最接近的因子变量, 该因子能够更好地反映研究对象.介绍了结构方程模型方法的原理, 并利用加拿大Nova Scotia省西南部湖泊沉积物地球化学数据建立了与热液型金矿有关的地球化学元素结构方程模型, 研究了结构方程模型所给出的组合变量空间分布规律以及与金矿床的关系.与主成分分析方法所给出的计算结果进行对比发现, 结构模型所计算的与金矿相关的组合变量与矿床的空间相关性较高, 并且对金矿床(矿点)也具有较好的预测性.      

米兰科维奇旋回时间序列分析法研究进展

时间序列分析法是米兰科维奇旋回（米氏旋回）研究的主要方法。它利用数学变换对地层数据序列进行定量分析,从而识别地质记录中天文驱动形成的旋回信号,为年代校准、地层划分和古气候研究等提供重要依据。针对米氏旋回研究中时间序列分析法的主要步骤,分别从地层序列的数据类型、天文检验及天文调谐等三方面,阐述了现有方法的基本原理,并总结了其优势和局限性。在基于时间序列分析的米氏旋回研究中,不同地层序列数据对天文轨道驱动和非天文噪声的响应具有差异性,综合利用多种数据指标中蕴含的地质信息有助于减小旋回分析中的不确定性;近年来涌现的新型天文检验和调谐方法促进了米氏旋回分析向定量化方向发展,但这些新方法仍需要进一步验证及改进。未来的工作中,地层数据序列的定量评价、多数据类型的信息优化等方面仍值得深入研究;面对多种时间序列分析方法,有效整合现有方法的同时,也需要引入新方法和新思路。